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Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems

Nico Aerts (UGent) , Iancu Avram (UGent) and Marc Moeneclaey (UGent)
(2014) EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING.
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Abstract
When estimating channel parameters in linearly modulated communication systems, the iterative expectation-maximization (EM) algorithm can be used to exploit the signal energy associated with the unknown data symbols. It turns out that the channel estimation requires at each EM iteration the a posteriori probabilities (APPs) of these data symbols, resulting in a high computational complexity when channel coding is present. In this paper, we present a new approximation of the APPs of trellis-coded symbols, which is less complex and requires less memory than alternatives from literature. By means of computer simulations, we show that the Viterbi decoder that uses the EM channel estimate resulting from this APP approximation experiences a negligible degradation in frame error rate (FER) performance, as compared to using the exact APPs in the channel estimation process.
Keywords
A posteriori symbol probability, ML estimation, ALGORITHM, CONVOLUTIONAL-CODES, Trellis-coded modulation, EM algorithm, Viterbi decoder

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MLA
Aerts, Nico, et al. “Low-Complexity a Posteriori Probability Approximation in EM-Based Channel Estimation for Trellis-Coded Systems.” EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2014, doi:10.1186/1687-1499-2014-153.
APA
Aerts, N., Avram, I., & Moeneclaey, M. (2014). Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems. EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING. https://doi.org/10.1186/1687-1499-2014-153
Chicago author-date
Aerts, Nico, Iancu Avram, and Marc Moeneclaey. 2014. “Low-Complexity a Posteriori Probability Approximation in EM-Based Channel Estimation for Trellis-Coded Systems.” EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING. https://doi.org/10.1186/1687-1499-2014-153.
Chicago author-date (all authors)
Aerts, Nico, Iancu Avram, and Marc Moeneclaey. 2014. “Low-Complexity a Posteriori Probability Approximation in EM-Based Channel Estimation for Trellis-Coded Systems.” EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING. doi:10.1186/1687-1499-2014-153.
Vancouver
1.
Aerts N, Avram I, Moeneclaey M. Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems. EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING. 2014;
IEEE
[1]
N. Aerts, I. Avram, and M. Moeneclaey, “Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems,” EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2014.
@article{5828092,
  abstract     = {{When estimating channel parameters in linearly modulated communication systems, the iterative expectation-maximization (EM) algorithm can be used to exploit the signal energy associated with the unknown data symbols. It turns out that the channel estimation requires at each EM iteration the a posteriori probabilities (APPs) of these data symbols, resulting in a high computational complexity when channel coding is present. In this paper, we present a new approximation of the APPs of trellis-coded symbols, which is less complex and requires less memory than alternatives from literature. By means of computer simulations, we show that the Viterbi decoder that uses the EM channel estimate resulting from this APP approximation experiences a negligible degradation in frame error rate (FER) performance, as compared to using the exact APPs in the channel estimation process.}},
  articleno    = {{153}},
  author       = {{Aerts, Nico and Avram, Iancu and Moeneclaey, Marc}},
  issn         = {{1687-1499}},
  journal      = {{EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING}},
  keywords     = {{A posteriori symbol probability,ML estimation,ALGORITHM,CONVOLUTIONAL-CODES,Trellis-coded modulation,EM algorithm,Viterbi decoder}},
  language     = {{eng}},
  pages        = {{7}},
  title        = {{Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems}},
  url          = {{http://dx.doi.org/10.1186/1687-1499-2014-153}},
  year         = {{2014}},
}
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